Ph.D. student M.Sc. Nina Hänninen has received a funding of 24 000 euros from the Finnish Cultural Foundation for the doctoral thesis on development of novel MRI contrasts for studying macromolecular structure of articular cartilage.

A new article “Osteoarthritis year in review 2018: imaging” by Miika Nieminen, Victor Casula V, Mika Nevalainen, and Simo Saarakkala has been accepted for publication in Osteoarthritis and Cartilage (DOI: 10.1016/j.joca.2018.12.009). This article provides a narrative review of the most relevant original research published in 2017/2018 on osteoarthritis imaging.

The MAKNEE team has been selected to be part of the main pitching competition in SLUSH: the 100 Pitching Competition. This event offers a unique opportunity to reach the global audience and engage with the tech community, investors, mentors and customers.

Furthermore, MAKNEE was selected as a finalist in the Y-Science pitching competition, which is a side event of Slush for life Sciences. The idea of this event is to bring forth the value of the science-based business, and encourage scientists to embrace a different way of thinking about impact.

During the stage time at the events, postdoc Jérôme Thevenot will have the opportunity to present the idea behind MAKNEE and the potential of this project to impact the society.

You can visit MAKNEE booth D29 at Slush the 5.12 to learn more about their non-invasive joint evaluation.

A significant 525 000 euro funding was granted by The Future Makers –programme by the Technology Industries of Finland Centennial Foundation and the Jane and Aatos Erkko Foundation for AIDMEI project, directed by professor Miika Nieminen from the University of Oulu. The goal is to develop a novel artificial intelligence-based workflow for the radiological diagnostics process leading to an accessible, more accurate, and affordable healthcare.

Artificial intelligence (AI) has gained a lot of interest in the field of medical imaging within the last few years. Due to the aging of the population, the number of medical images taken from patients as well as the complexity of imaging analysis and associated data therein are increasing. Medical professionals spend more time for diagnostics leading to reduced time with patients and research.

In the AIDMEI project, the Research Unit of Medical Imaging, Physics and Technology from the University of Oulu, Oulu University Hospital and University of Helsinki are developing a novel artificial intelligence-based workflow. This research opening has potential to revolutionize the radiological diagnostics process by training AI with a unique, existing annotated imaging data archived at the Oulu University Hospital.

AIDMEI targets two clinically relevant use cases where AI based methodologies are being developed for MRI diagnostics of prolonged back pain and mammography diagnostics of breast cancer. AI is used to improve reconstructed image quality for presentation, and for extracting important quantitative features from medical images for automated diagnosis.

As an outcome of this project, intelligent algorithms will assist in time constraints, increasing workload, and other limitations pertaining to human driven diagnostics. Artificial intelligence guided diagnostic workflow could lead to an accessible, more accurate, and affordable healthcare for everyone.

In addition to professor Miika Nieminen, professors Simo Saarakkala, Osmo Tervonen, Jaro Karppinen and Jarmo Reponen from the University of Oulu, and professor Samuli Siltanen from The Department of Mathematics and Statistics, The University of Helsinki, participate in the project.